Python Pandas: any(axis='rows') and any(axis='columns') give counter-intuitive outputs

Question

Consider the following outputs:

This is opposite to what I expect.

• If you're checking along the rows, and there are 3 rows, shouldn't you produce 3 Booleans?
• If you're checking along the columns, and there are 2 columns, shouldn't you produce 2 Booleans?

Please explain this seemingly counter-intuitive logic.